Mark Hansen: How Generative AI Can Help With Data Journalism

Mark Hansen joins Nikita Roy to discuss how generative AI can enhance data journalism, particularly by accelerating coding tasks. The discussion also addresses bias and privacy concerns associated with AI models.

Mark is the East Coast Director of The Brown Institute for Media Innovation, a collaborative initiative between Columbia Journalism School and Stanford's School of Engineering. 

Mark began his tenure at Columbia Journalism School over a decade ago, serving as a Professor and teaching computational and data journalism courses.

An investigation in one of his classes examining the bot economy behind the sale of fake followers on Twitter garnered significant attention. 

It became a front-page story in the New York Times and was part of a package of stories that secured the 2019 Polk Award for National Reporting. Additionally, it was shortlisted for the 2019 Pulitzer Prize for National Reporting.

Mark Hansen earned his Ph.D. in Statistics from the University of California, Berkeley, and a BS in Applied Mathematics from the University of California, Davis.

Referenced:

Sorting Things Out: Classification and Its Consequences by Geoffrey C. Bowker and Susan Leigh Star

Seeing Like a State: How Certain Schemes to Improve the Human Condition Have Failed by James C. Scott

Data Feminism by Catherine D'Ignazio and Lauren Klein

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